We evaluated 5 transfer schemes of different types: (1) Random Search (RS) [1]}; (2) Direct transfer of top architectures (DT); (3) Direct policy transfer of reinforcement learning-based algorithm, e.g., Proximal Policy Optimization (PPO) [2]}; (4) Meta-learning based algorithm, e.g., CATCH [3]}; (5) Evolutionary algorithms with transferred population initialization, e.g., Regularized Evolutionary Algorithm (REA) [4]}. Each selected algorithm represents a distinctive type of transfer scheme, and they are compatible with both search spaces. The algorithms are tested using the MindSpore tools [5]}.
